The Mucosal Adjuvant Activities of ADP-Ribosylating Bacterial Enterotoxins
Bibliographic record
Abstract
The bacterial enterotoxins, cholera toxin and the heat labile toxin of E. coli, are well known adjuvants for mucosal immune response. Their common A chain mediates the toxigenic mechanism by causing ADP ribosylation of G proteins and subsequent elevation of cAMP in target cells. A large IgA and IgG antibody response to admixed protein antigen (Ag) is the hallmark of these adjuvants and is clearly associated with the A chain activity. Expansion of Ag-specific B and T cells, alteration of T cell cytokine production, and changes in regulatory T cells have been reported as adjuvant mechanisms. The B chain derivatives of these toxins can also weakly enhance immune response, especially if covalently associated with Ag and used for nasophyrangeal immunization. Importantly, these toxins or their B chain derivatives can alter the normal immune regulation that produces oral tolerance. This indicates that they modulate mechanisms operative between the mucosal and systemic immune systems. There are some discrepancies between in vitro models of CT or LT activity and in vivo manifestations of their adjuvant activities. Interpretation of current data regarding in vivo mechanism is hampered by an incomplete understanding of how mucosal B and T cells can interact with systemic lymphoid tissue and vice versa. More important, there is no clear understanding of the early effects of the toxins on the local (and draining) mucosal lymphoid tissues. This is especially true in the critical areas of antigen presentation, T and B cell activation, and cytokine production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".